Context-dependent incremental intention recognition through bayesian network model construction

Han The Anh, Luís Moniz Pereira

Research output: Contribution to journalConference articlepeer-review

8 Citations (Scopus)


We present a method for context-dependent and incremental intention recognition by means of incrementally constructing a Bayesian Network (BN) model as more actions are observed. It is achieved with the support of a knowledge base of readily maintained and constructed fragments of BNs. The simple structure of the fragments enables to easily and efficiently acquire the knowledge base, either from domain experts or automatically from a plan corpus. We exhibit experimental results improvement for the Linux Plan corpus. For additional experimentation, new plan corpora for the iterated Prisoner's Dilemma are created. We show that taking into account contextual information considerably increases intention recognition performance.

Original languageEnglish
Pages (from-to)50-58
Number of pages9
JournalCEUR Workshop Proceedings
Publication statusPublished - 14 Jul 2011
Event8th Bayesian Modeling ApplicationsWorkshop, BMAW 2011 - Barcelona, Spain
Duration: 14 Jul 201114 Jul 2011


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